Neural network and genetic algorithm as a new approach in design optimization of induction machines (CROSBI ID 490095)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Smajić, Jasmin ; Berberović, Sead ; Madžarević , Vlado ; Kapetanović , Izudin ; Haznadar , Zijad ; Tokić , Amir
engleski
Neural network and genetic algorithm as a new approach in design optimization of induction machines
A new approach for optimization of induction machines is presented in this paper.This algorithm is based on the neural networks and genetic algorithm.Neural networks are used as a tool for prediction of induction machine characteristics with respect to induction machine geometrical variables.The optimization process is based on genetic algorithm, as a method from the category of probabilistic algorithms.Optimization algorithm is tested on the optimization of double-cage induction machine starting characteristics.Numerical calculations of induction machine starting characteristics, as an important part of this algorithm, are performed using finite element method for electromagnetic field computation inside of induction machine.Results of electromagnetic field computation are used for synthesis of induction machine equivalent circuit.Full algorithm for calculation of induction machine starting characteristics is developed and named as &#8220 ; voltage balanced iterative process &#8221 ; . Results of starting characteristics calculation are compared with results of experimental measurement. Result of optimization process is induction motor with better starting performances.
design; software; neural networks; induction motors
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Podaci o prilogu
2002.
objavljeno
Podaci o matičnoj publikaciji
Benčić, Zvonko
Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu
Podaci o skupu
10th International Power Electronics and Motion Control Conference EPE-PEMC 2002
predavanje
09.09.2002-11.09.2002
Dubrovnik, Hrvatska; Cavtat, Hrvatska